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[2005.01643] Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

ar5iv.labs.arxiv.org · 41,665 words · saved by 1 readers

In this tutorial article, we aim to provide the reader with the conceptual tools needed to get started on research on offline reinforcement learning algorithms: reinforcement learning algorithms that utilize previously…

\stackMath Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine 1,2 , Aviral Kumar 1 , George Tucker 2 , Justin Fu 1 1 UC Berkeley, 2 Google Research, Brain Team Abstract In this tutorial article, we aim to provide the reader with the conceptual tools needed to get started on research on offline reinforcement learning algorithms: reinforcement learning algorithms that utilize previously collected data, without additional online data collection. Offline reinforcement learning algorithms hold tremendous promise for making it possible to turn large dat

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